标题： 解密配送移动性：即时配送骑手的城市规模路径重构轨迹数据集 显示英文标题

标题： Deciphering Delivery Mobility: A City-Scale, Path-Reconstructed Trajectory Dataset of Instant Delivery Riders

摘要： 按需经济的迅速扩张深刻重塑了城市交通和物流，然而关于配送骑手持续移动的高分辨率轨迹数据仍然稀缺。 在此，我们呈现了一个北京市规模的、高分辨率的按需即时配送骑手时空轨迹数据集。 该数据集是通过对包含配送订单信息的公开数据集应用路径重构方法生成的。 随后，通过模拟主要在线地图服务的骑行路线，重建了详细且连续的轨迹，以确保它们与实际状况相符。 为了验证，将重建的路径与地面真实旅行指标进行比较，显示出与实际旅行模式的高度相关性。 分析得出路线距离的皮尔逊相关系数为0.92，路线时长的皮尔逊相关系数为0.79。 这种高保真度确保了该数据集在描述配送骑手移动方面的实用性。 这一公开资源为城市规划、交通研究、物流优化和计算社会科学领域的研究人员提供了前所未有的机会，以研究骑手行为、建模城市货运系统，并开发更高效和可持续的城市物流解决方案。 显示英文摘要

摘要： The rapid expansion of the on-demand economy has profoundly reshaped urban mobility and logistics, yet high-resolution trajectory data on delivery riders' consistent movements remains scarce. Here, we present a city-scale, high-resolution spatiotemporal trajectory dataset of on-demand instant delivery riders in Beijing. This dataset was produced through a path-reconstruction methodology applied to an open dataset containing delivery order information. Subsequently, detailed and continuous trajectories were reconstructed by simulating cycling routes via a major online map service to ensure they were realistically aligned. For validation, the reconstructed paths were compared against ground-truth travel metrics, revealing a strong correlation with actual travel patterns. The analysis yielded Pearson correlation coefficients of 0.92 for route distance and 0.79 for route duration. This high fidelity ensures the dataset's utility for describing delivery riders' mobility. This publicly available resource offers unprecedented opportunities for researchers in urban planning, transportation studies, logistics optimization, and computational social science to investigate rider behavior, model urban freight systems, and develop more efficient and sustainable city-wide logistics solutions.